100+ datasets found
  1. U.S. Senators 1975-2023, by race and ethnicity

    • statista.com
    Updated Feb 25, 2025
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    Statista (2025). U.S. Senators 1975-2023, by race and ethnicity [Dataset]. https://www.statista.com/statistics/198430/senators-in-the-us-congress-by-ethnic-group-since-1975/
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    Dataset updated
    Feb 25, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    There are 100 Senators that serve in the United States Congress at any given time - two from each of the fifty states. As of the first day of the 118th Congress, there were three African American Senators, two Asian American Senators, and six Hispanic Senators.

  2. U.S. number of women in the Senate 2025, by race and ethnicity

    • statista.com
    Updated Jul 10, 2025
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    Statista (2025). U.S. number of women in the Senate 2025, by race and ethnicity [Dataset]. https://www.statista.com/statistics/952975/number-women-color-us-senate-ethnicity/
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    Dataset updated
    Jul 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2025
    Area covered
    United States
    Description

    The number of women in the United States Senate has been increasing in recent years. In 2025, there were ** women serving in the United States Senate. Of those, * identified as Latina, and two as Black.

  3. U.S. House of Representatives members 2001-2023, by race and ethnicity

    • statista.com
    Updated Jul 9, 2025
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    Statista (2025). U.S. House of Representatives members 2001-2023, by race and ethnicity [Dataset]. https://www.statista.com/statistics/198437/representatives-in-the-us-congress-by-ethnic-group-since-1975/
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    Dataset updated
    Jul 9, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    There are *** members of the House of Representatives in any congressional sitting. In the ***** Congress which began in January 2023, there were ** Black members, ** Asian American members, ** Hispanic members.

  4. m

    US Senators

    • maconinsights.com
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • +3more
    Updated Mar 5, 2018
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    Macon-Bibb County Government (2018). US Senators [Dataset]. https://www.maconinsights.com/datasets/us-senators-1/api
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    Dataset updated
    Mar 5, 2018
    Dataset authored and provided by
    Macon-Bibb County Government
    Area covered
    Description

    Us Senators serving Macon-Bibb County.The two Senators that serve the State of Georgia are Johnny Isakson and David Perdue.The United States Senate is the upper chamber of the United States Congress, which along with the United States House of Representatives—the lower chamber—comprise the legislature of the United States.The composition and powers of the Senate are established by Article One of the United States Constitution. The Senate is composed of senators, each of whom represents a single state in its entirety, with each state being equally represented by two senators, regardless of its population, serving staggered terms of six years; with fifty states presently in the Union, there are 100 U.S. Senators. From 1789 until 1913, Senators were appointed by legislatures of the states they represented; following the ratification of the Seventeenth Amendment in 1913, they are now popularly elected. The Senate chamber is located in the north wing of the Capitol, in Washington, D.C.As the upper house, the Senate has several powers of advice and consent which are unique to it; these include the ratification of treaties and the confirmation of Cabinet secretaries, Supreme Court justices, federal judges, other federal executive officials, flag officers, regulatory officials, ambassadors, and other federal uniformed officers. In addition to these, in cases wherein no candidate receives a majority of electors for Vice President, the duty befalls upon the Senate to elect one of the top two recipients of electors for that office. It further has the responsibility of conducting trials of those impeached by the House. The Senate is widely considered both a more deliberative and more prestigious body than the House of Representatives due to its longer terms, smaller size, and statewide constituencies, which historically led to a more collegial and less partisan atmosphere.The presiding officer of the Senate is the Vice President of the United States, who is President of the Senate. In the Vice President's absence, the President Pro Tempore, who is customarily the senior member of the party holding a majority of seats, presides over the Senate. In the early 20th century, the practice of majority and minority parties electing their floor leaders began, although they are not constitutional officers.

  5. CBS News/New York Times New York State Poll, April 2000

    • icpsr.umich.edu
    ascii, delimited, sas +2
    Updated Jul 28, 2009
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    CBS News/New York Times New York State Poll, April 2000 [Dataset]. https://www.icpsr.umich.edu/web/ICPSR/studies/2981/staff
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    spss, stata, sas, delimited, asciiAvailable download formats
    Dataset updated
    Jul 28, 2009
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/2981/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/2981/terms

    Time period covered
    Apr 1, 2000 - Apr 5, 2000
    Area covered
    New York
    Description

    This special topic poll, fielded April 1-5, 2000, queried residents of New York State on the prospective Senate race between First Lady Hillary Rodham Clinton and New York City Mayor Rudolph Giuliani in 2000, and on a range of other political and social issues. Respondents were asked to give their opinions of President Bill Clinton, New York State governor George Pataki, Hillary Clinton, Rudolph Giuliani, and civil rights activist Al Sharpton. Regarding the upcoming Senate race, respondents were asked how much attention they were paying to the upcoming election, for whom they would vote, whether that decision was firm, and who they thought would win. Respondents were also asked which of the potential candidates cared more about people like the respondent, whether the candidates cared about the needs and problems of Black people, and whether the candidates were trying to bring together or divide various groups of New Yorkers. Respondents were asked whether they approved or disapproved of the way Giuliani was handling his job as mayor, and the way he was handling crime, education, and race relations. Regarding Mrs. Clinton, respondents were asked whether they approved of the way she was handling her role as First Lady. Opinions were also elicited on whether Hillary Clinton and Giuliani were spending more time explaining what they would do as senator or attacking each other. Respondents were asked to rate the performance of the New York City police department, whether the police should interfere in individuals' freedoms to make the city safer, and if the respondent had ever been insulted by an officer, felt in personal danger from a police officer, or felt safer because of a police officer. Other questions focused on whether racial profiling was widespread in New York City, whether racial profiling was justified, whether respondents had personally been racially profiled, and if the police favored whites over Blacks or Blacks over whites. In relation to the police shooting death of Patrick Dorismond, an unarmed Black male, outside of a Manhattan bar, respondents were asked how closely they had been following the shooting, how common brutality by the New York City police department against minorities was, how the policies of the Giuliani administration affected the amount of police brutality in New York City, whether the officer involved in the Dorismond shooting should face criminal charges, and whether the public comments made by Giuliani, Hillary Clinton, and Sharpton regarding the shooting made the situation better or worse. Background information on respondents includes voter registration and participation history, political party, political orientation, marital status, religion, education, age, sex, race, Hispanic descent, and family income.

  6. U.S. Wisconsin Senate race polling November 2024

    • statista.com
    Updated Nov 5, 2024
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    Statista (2024). U.S. Wisconsin Senate race polling November 2024 [Dataset]. https://www.statista.com/statistics/1488584/wisconsin-senate-race-polling-2024/
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    Dataset updated
    Nov 5, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Oct 16, 2024 - Nov 4, 2024
    Area covered
    United States
    Description

    On November 5, 2024, Senate elections will be held in the state of Wisconsin. As of November polling, Democratic incumbent Tammy Baldwin was leading Republican bank owner Eric Hovde by almost two percentage points. This race is one of the 15 Democratic-held U.S. Senate seats up for election in 2024, and is crucial for Democrats to remain the Senate majority in 2024.

  7. U.S. midterm election Senate races with most money spent 2022

    • statista.com
    Updated Sep 15, 2022
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    Statista (2022). U.S. midterm election Senate races with most money spent 2022 [Dataset]. https://www.statista.com/statistics/1318120/midterm-senate-races-most-money-spent-us/
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    Dataset updated
    Sep 15, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    As of December 2022, the United States Senate race in Georgia spent the highest amount of funds in the midterm election cycle, followed by Pennsylvania and Florida. Pennsylvania and Georgia both played a key roll in securing Democrats a Senate majority after the 2022 midterms.

  8. Senate, House, and Governor Race Candidates From Across the United States,...

    • icpsr.umich.edu
    • search.datacite.org
    ascii, delimited, sas +2
    Updated May 8, 2008
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    Latimer, Christopher (2008). Senate, House, and Governor Race Candidates From Across the United States, 2002 [Dataset]. http://doi.org/10.3886/ICPSR21000.v1
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    spss, stata, delimited, sas, asciiAvailable download formats
    Dataset updated
    May 8, 2008
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    Latimer, Christopher
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/21000/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/21000/terms

    Time period covered
    2002
    Area covered
    United States
    Description

    This study considers the growing potential of the Internet in United States elections at the sub-presidential level and whether the Internet can be used as an effective tool in campaigns and elections. Internet sites for incumbents, challengers, and third-party candidates were closely examined and compared on several dimensions of quality. Using a sample of sites collected in the 2002 elections, a comprehensive tool was developed to assess Internet quality using both analytical criteria and statistical checks. Five dimensions were examined: content, interactivity, usability, transparency, and audience. This analysis of the 2002 United States election Web sites focuses on the contests for the House of Representatives, the Senate, and for governor in those states with scheduled elections. The dataset includes 111 separate races: 84 for the House, 12 for the Senate and 16 for governor. There are 245 individual House candidates, 62 gubernatorial candidates, and 45 individual Senate candidates. This dataset also explores the relationship between Internet quality and the political and demographic features of a district. Internet quality also is evaluated in relation to other significant resources in a candidate's campaign, e.g., years of service, incumbency, political party, competition, and campaign finance. House races were isolated in order to evaluate the relationship between Internet quality, these significant political resources, and demographic aspects of the districts. Shifting the level of analysis from the candidate to the district examined how short-term elements of campaigns, including a candidate's Web site, interact and correlate with political features of a contest and demographic features of a congressional district.

  9. f

    Race/Ethnicity (by Georgia Senate) 2017

    • gisdata.fultoncountyga.gov
    Updated Jun 21, 2019
    + more versions
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    Georgia Association of Regional Commissions (2019). Race/Ethnicity (by Georgia Senate) 2017 [Dataset]. https://gisdata.fultoncountyga.gov/datasets/GARC::race-ethnicity-by-georgia-senate-2017/explore
    Explore at:
    Dataset updated
    Jun 21, 2019
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2013-2017, to show population by race/ethnicity and change data by Georgia Senate in the Atlanta region. The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2013-2017). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website. Naming conventions: Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)Suffixes:NoneChange over two periods_eEstimate from most recent ACS_mMargin of Error from most recent ACS_00Decennial 2000 Attributes: SumLevelSummary level of geographic unit (e.g., County, Tract, NSA, NPU, DSNI, SuperDistrict, etc)GEOIDCensus tract Federal Information Processing Series (FIPS) code NAMEName of geographic unitPlanning_RegionPlanning region designation for ARC purposesAcresTotal area within the tract (in acres)SqMiTotal area within the tract (in square miles)CountyCounty identifier (combination of Federal Information Processing Series (FIPS) codes for state and county)CountyNameCounty NameTotPop_e# Total population, 2017TotPop_m# Total population, 2017 (MOE)Hisp_e# Hispanic or Latino (of any race), 2017Hisp_m# Hispanic or Latino (of any race), 2017 (MOE)pHisp_e% Hispanic or Latino (of any race), 2017pHisp_m% Hispanic or Latino (of any race), 2017 (MOE)Not_Hisp_e# Not Hispanic or Latino, 2017Not_Hisp_m# Not Hispanic or Latino, 2017 (MOE)pNot_Hisp_e% Not Hispanic or Latino, 2017pNot_Hisp_m% Not Hispanic or Latino, 2017 (MOE)NHWhite_e# Not Hispanic, White alone, 2017NHWhite_m# Not Hispanic, White alone, 2017 (MOE)pNHWhite_e% Not Hispanic, White alone, 2017pNHWhite_m% Not Hispanic, White alone, 2017 (MOE)NHBlack_e# Not Hispanic, Black or African American alone, 2017NHBlack_m# Not Hispanic, Black or African American alone, 2017 (MOE)pNHBlack_e% Not Hispanic, Black or African American alone, 2017pNHBlack_m% Not Hispanic, Black or African American alone, 2017 (MOE)NH_AmInd_e# Not Hispanic, American Indian and Alaska Native alone, 2017NH_AmInd_m# Not Hispanic, American Indian and Alaska Native alone, 2017 (MOE)pNH_AmInd_e% Not Hispanic, American Indian and Alaska Native alone, 2017pNH_AmInd_m% Not Hispanic, American Indian and Alaska Native alone, 2017 (MOE)NH_Asian_e# Not Hispanic, Asian alone, 2017NH_Asian_m# Not Hispanic, Asian alone, 2017 (MOE)pNH_Asian_e% Not Hispanic, Asian alone, 2017pNH_Asian_m% Not Hispanic, Asian alone, 2017 (MOE)NH_PacIsl_e# Not Hispanic, Native Hawaiian and Other Pacific Islander alone, 2017NH_PacIsl_m# Not Hispanic, Native Hawaiian and Other Pacific Islander alone, 2017 (MOE)pNH_PacIsl_e% Not Hispanic, Native Hawaiian and Other Pacific Islander alone, 2017pNH_PacIsl_m% Not Hispanic, Native Hawaiian and Other Pacific Islander alone, 2017 (MOE)NH_OthRace_e# Not Hispanic, some other race alone, 2017NH_OthRace_m# Not Hispanic, some other race alone, 2017 (MOE)pNH_OthRace_e% Not Hispanic, some other race alone, 2017pNH_OthRace_m% Not Hispanic, some other race alone, 2017 (MOE)NH_TwoRace_e# Not Hispanic, two or more races, 2017NH_TwoRace_m# Not Hispanic, two or more races, 2017 (MOE)pNH_TwoRace_e% Not Hispanic, two or more races, 2017pNH_TwoRace_m% Not Hispanic, two or more races, 2017 (MOE)NH_AsianPI_e# Non-Hispanic Asian or Pacific Islander, 2017NH_AsianPI_m# Non-Hispanic Asian or Pacific Islander, 2017 (MOE)pNH_AsianPI_e% Non-Hispanic Asian or Pacific Islander, 2017pNH_AsianPI_m% Non-Hispanic Asian or Pacific Islander, 2017 (MOE)NH_Other_e# Non-Hispanic other (Native American, other one race, two or more races), 2017NH_Other_m# Non-Hispanic other (Native American, other one race, two or more races), 2017 (MOE)pNH_Other_e% Non-Hispanic other (Native American, other one race, two or more races), 2017pNH_Other_m% Non-Hispanic other (Native American, other one race, two or more races), 2017 (MOE)last_edited_dateLast date the feature was edited by ARC Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2013-2017 For additional information, please visit the Census ACS website.

  10. a

    United States Senator

    • share-open-data-crawfordcountypa.opendata.arcgis.com
    • hub.arcgis.com
    Updated Jan 14, 2019
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    Crawford County Government (2019). United States Senator [Dataset]. https://share-open-data-crawfordcountypa.opendata.arcgis.com/datasets/united-states-senator/data
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    Dataset updated
    Jan 14, 2019
    Dataset authored and provided by
    Crawford County Government
    Area covered
    Description

    Unofficial election results of the US Senate race - 2018 General Election within Crawford County PA. All election results are unofficial until certified by the Election Board

  11. A

    ‘🗳 Primary Candidates’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Sep 27, 2018
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2018). ‘🗳 Primary Candidates’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-primary-candidates-1257/092d1aca/?iid=023-113&v=presentation
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    Dataset updated
    Sep 27, 2018
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Analysis of ‘🗳 Primary Candidates’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/primary-candidatese on 28 January 2022.

    --- Dataset description provided by original source is as follows ---

    About this dataset

    This folder contains the data behind the stories:

    This project looks at patterns in open Democratic and Republican primary elections for the U.S. Senate, U.S. House and governor in 2018.

    dem_candidates.csv contains information about the 811 candidates who have appeared on the ballot this year in Democratic primaries for Senate, House and governor, not counting races featuring a Democratic incumbent, as of August 7, 2018.

    rep_candidates.csv contains information about the 774 candidates who have appeared on the ballot this year in Republican primaries for Senate, House and governor, not counting races featuring a Republican incumbent, through September 13, 2018.

    Here is a description and source for each column in the accompanying datasets.

    dem_candidates.csv and rep_candidates.csv include:

    ColumnDescription
    CandidateAll candidates who received votes in 2018’s Democratic primary elections for U.S. Senate, U.S. House and governor in which no incumbent ran. Supplied by Ballotpedia.
    StateThe state in which the candidate ran. Supplied by Ballotpedia.
    DistrictThe office and, if applicable, congressional district number for which the candidate ran. Supplied by Ballotpedia.
    Office TypeThe office for which the candidate ran. Supplied by Ballotpedia.
    Race TypeWhether it was a “regular” or “special” election. Supplied by Ballotpedia.
    Race Primary Election DateThe date on which the primary was held. Supplied by Ballotpedia.
    Primary StatusWhether the candidate lost (“Lost”) the primary or won/advanced to a runoff (“Advanced”). Supplied by Ballotpedia.
    Primary Runoff Status“None” if there was no runoff; “On the Ballot” if the candidate advanced to a runoff but it hasn’t been held yet; “Advanced” if the candidate won the runoff; “Lost” if the candidate lost the runoff. Supplied by Ballotpedia.
    General Status“On the Ballot” if the candidate won the primary or runoff and has advanced to November; otherwise, “None.” Supplied by Ballotpedia.
    Primary %The percentage of the vote received by the candidate in his or her primary. In states that hold runoff elections, we looked only at the first round (the regular primary). In states that hold all-party primaries (e.g., California), a candidate’s primary percentage is the percentage of the total Democratic vote they received. Unopposed candidates and candidates nominated by convention (not primary) are given a primary percentage of 100 but were excluded from our analysis involving vote share. Numbers come from official results posted by the secretary of state or local elections authority; if those were unavailable, we used unofficial election results from the New York Times.
    Won Primary“Yes” if the candidate won his or her primary and has advanced to November; “No” if he or she lost.

    dem_candidates.csv includes:

    ColumnDescription
    Gender“Male” or “Female.” Supplied by Ballotpedia.
    Partisan LeanThe FiveThirtyEight partisan lean of the district or state in which the election was held. Partisan leans are calculated by finding the average difference between how a state or district voted in the past two presidential elections and how the country voted overall, with 2016 results weighted 75 percent and 2012 results weighted 25 percent.
    Race“White” if we identified the candidate as non-Hispanic white; “Nonwhite” if we identified the candidate as Hispanic and/or any nonwhite race; blank if we could not identify the candidate’s race or ethnicity. To determine race and ethnicity, we checked each candidate’s website to see if he or she identified as a certain race. If not, we spent no more than two minutes searching online news reports for references to the candidate’s race.
    Veteran?If the candidate’s website says that he or she served in the armed forces, we put “Yes.” If the website is silent on the subject (or explicitly says he or she didn’t serve), we put “No.” If the field was left blank, no website was available.
    LGBTQ?If the candidate’s website says that he or she is LGBTQ (including indirect references like to a same-sex partner), we put “Yes.” If the website is silent on the subject (or explicitly says he or she is straight), we put “No.” If the field was left blank, no website was available.
    Elected Official?We used Ballotpedia, VoteSmart and news reports to research whether the candidate had ever held elected office before, at any level. We put “Yes” if the candidate has held elected office before and “No” if not.
    Self-Funder?We used Federal Election Committee fundraising data (for federal candidates) and state campaign-finance data (for gubernatorial candidates) to look up how much each candidate had invested in his or her own campaign, through either donations or loans. We put “Yes” if the candidate donated or loaned a cumulative $400,000 or more to his or her own campaign before the primary and “No” for all other candidates.
    STEM?If the candidate identifies on his or her website that he or she has a background in the fields of science, technology, engineering or mathematics, we put “Yes.” If not, we put “No.” If the field was left blank, no website was available.
    Obama Alum?We put “Yes” if the candidate mentions working for the Obama administration or campaign on his or her website, or if the candidate shows up on this list of Obama administration members and campaign hands running for office. If not, we put “No.”
    Dem Party Support?“Yes” if the candidate was placed on the DCCC’s Red to Blue list before the primary, was endorsed by the DSCC before the primary, or if the DSCC/DCCC aired pre-primary ads in support of the candidate. (Note: according to the DGA’s press secretary, the DGA does not get involved in primaries.) “No” if the candidate is running against someone for whom one of the above things is true, or if one of those groups specifically anti-endorsed or spent money to attack the candidate. If those groups simply did not weigh in on the race, we left the cell blank.
    Emily Endorsed?“Yes” if the candidate was endorsed by Emily’s List before the primary. “No” if the candidate is running against an Emily-endorsed candidate or if Emily’s List specifically anti-endorsed or spent money to attack the candidate. If Emily’s List simply did not weigh in on the race, we left the cell blank.
    Gun Sense Candidate?“Yes” if the candidate received the Gun Sense Candidate Distinction from Moms Demand Action/Everytown for Gun Safety before the primary, according to media reports or the candidate’s website. “No” if the candidate is running against an candidate with the distinction. If Moms Demand Action simply did not weigh in on the race, we left the cell blank.
    Biden Endorsed?“Yes” if the candidate was endorsed by Joe Biden before the primary. “No” if the candidate is running against a Biden-endorsed candidate or if Biden specifically anti-endorsed the candidate. If Biden simply did not weigh in on the race, we left the cell blank.
    Warren Endorsed?“Yes” if the candidate was endorsed by Elizabeth Warren before the primary. “No” if the candidate is running against a Warren-endorsed candidate or if Warren specifically anti-endorsed the candidate. If Warren simply did not weigh in on the race, we left the cell blank.
    Sanders Endorsed?“Yes” if the candidate was endorsed by Bernie Sanders before the primary. “No” if the candidate is running against a Sanders-endorsed candidate or if Sanders specifically anti-endorsed the candidate. If Sanders simply did not weigh in on the race, we left the cell

  12. CBS News/New York Times New Jersey State Survey, October 2002

    • icpsr.umich.edu
    ascii, delimited, sas +2
    Updated Apr 29, 2009
    + more versions
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    Inter-university Consortium for Political and Social Research [distributor] (2009). CBS News/New York Times New Jersey State Survey, October 2002 [Dataset]. http://doi.org/10.3886/ICPSR03709.v3
    Explore at:
    stata, delimited, ascii, sas, spssAvailable download formats
    Dataset updated
    Apr 29, 2009
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/3709/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/3709/terms

    Time period covered
    Oct 2002
    Area covered
    New Jersey, United States
    Description

    This special topic poll is part of a continuing series of monthly surveys that solicit public opinion on the presidency and a range of other political and social issues. The study was conducted in part to assess respondents' interest in and opinions about the 2002 elections in New Jersey. Residents of that state were asked to give their opinions of President George W. Bush and his handling of the presidency, as well as their views of United States Senators Jon Corzine and Robert Torricelli, New Jersey governor Jim McGreevey, and former United States Senator Frank Lautenberg. Those queried were asked whether they intended to vote in the November 5, 2002, elections, and for whom they would vote if the election for United States Senator were held that day, given a choice between Lautenberg (Democratic Party) and Douglas Forrester (Republican Party). Respondents were also asked if Lautenberg and Forrester had spent more time during the campaign attacking each other or explaining what they would do if elected, whether they found the Senate race interesting or dull, what they considered to be the most important issue in deciding how to vote, and whether they considered their vote as a vote for or against Bush. Those polled answered sets of questions comparing Lautenberg and Forrester as Senate candidates in terms of their experience, honesty, integrity, age, political orientation, position on Iraq, and their potential decisions on United States Supreme Court nominees. A series of questions addressed the withdrawal of Torricelli from the Senate race and Lautenberg's replacement of him: whether Torricelli did the right thing by withdrawing, whether it was fair that the Democrats replaced him on the ballot, whether the New Jersey Supreme Court made the right decision by allowing his replacement, and whether that decision had made a difference in how the respondent intended to vote. Respondents' views were sought on the use of tax dollars to pay for abortions for indigent women, increased restrictions on the sale of handguns, whether the sentence for a murder conviction should be the death penalty or life in prison without parole, whether companies responsible for major pollution problems should be held accountable for the clean-up costs, and whether the government should cover losses incurred by individuals who chose to invest their Social Security taxes in the stock market. Additional questions probed respondents' views on corruption in New Jersey politics, the importance of which political party controls the United States Congress, the influence of Lautenberg and Forrester campaign advertisements, and whether the respondent would vote for musician Bruce Springsteen if he were a candidate for United States Senator from New Jersey. Background information on respondents includes age, gender, political party, political orientation, voter registration and participation history, handgun ownership, education, religion, marital status, Hispanic descent, race, years in community, and household income.

  13. a

    Social by Race (by Georgia Senate) 2017

    • opendata.atlantaregional.com
    Updated Jun 26, 2019
    + more versions
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    Georgia Association of Regional Commissions (2019). Social by Race (by Georgia Senate) 2017 [Dataset]. https://opendata.atlantaregional.com/datasets/GARC::social-by-race-by-georgia-senate-2017/about
    Explore at:
    Dataset updated
    Jun 26, 2019
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2013-2017, to show school enrollment, education attainments, and household composition by race and by Georgia Senate Districts.

    The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent.

    The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2013-2017). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

    For further explanation of ACS estimates and margin of error, visit Census ACS website.

    Naming conventions:

    Prefixes:

    None

    Count

    p

    Percent

    r

    Rate

    m

    Median

    a

    Mean (average)

    t

    Aggregate (total)

    ch

    Change in absolute terms (value in t2 - value in t1)

    pch

    Percent change ((value in t2 - value in t1) / value in t1)

    chp

    Change in percent (percent in t2 - percent in t1)

    Suffixes:

    None

    Change over two periods

    _e

    Estimate from most recent ACS

    _m

    Margin of Error from most recent ACS

    _00

    Decennial 2000

    Attributes:

    Attributes and definitions available below under "Attributes" section and in Infrastructure Manifest (due to text box constraints, attributes cannot be displayed here).

    Source: U.S. Census Bureau, Atlanta Regional Commission

    Date: 2013-2017

    For additional information, please visit the Census ACS website.

  14. U.S. Florida Senate race polling November 2024

    • statista.com
    Updated Nov 5, 2024
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    Statista (2024). U.S. Florida Senate race polling November 2024 [Dataset]. https://www.statista.com/statistics/1488589/florida-senate-race-polling-2024/
    Explore at:
    Dataset updated
    Nov 5, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    On November 5, 2024, Senate elections will be held in the state of Florida. As of November polling, Republican incumbent Rick Scott was leading Democratic former congresswoman Debbie Mucarsel-Powell by four percentage points. This race is one of the nine Republican-held U.S. Senate seats up for election in 2024.

  15. a

    Economic by Race (by Georgia Senate) 2017

    • opendata.atlantaregional.com
    • gisdata.fultoncountyga.gov
    Updated Jun 25, 2019
    + more versions
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    Georgia Association of Regional Commissions (2019). Economic by Race (by Georgia Senate) 2017 [Dataset]. https://opendata.atlantaregional.com/datasets/economic-by-race-by-georgia-senate-2017/explore
    Explore at:
    Dataset updated
    Jun 25, 2019
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2013-2017, to show numbers and percentages for occupation, household income, and commuting pattern by race and by Georgia Senate in the Atlanta region.

    The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent.

    The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2013-2017). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

    For further explanation of ACS estimates and margin of error, visit Census ACS website.

    Naming conventions:

    Prefixes:

    None

    Count

    p

    Percent

    r

    Rate

    m

    Median

    a

    Mean (average)

    t

    Aggregate (total)

    ch

    Change in absolute terms (value in t2 - value in t1)

    pch

    Percent change ((value in t2 - value in t1) / value in t1)

    chp

    Change in percent (percent in t2 - percent in t1)

    Suffixes:

    None

    Change over two periods

    _e

    Estimate from most recent ACS

    _m

    Margin of Error from most recent ACS

    _00

    Decennial 2000

    Attributes:

    Attributes and definitions available below under "Attributes" section and in Infrastructure Manifest (due to text box constraints, attributes cannot be displayed here).

    Source: U.S. Census Bureau, Atlanta Regional Commission

    Date: 2013-2017

    For additional information, please visit the Census ACS website.

  16. a

    OCACS 2017 Demographic Characteristics for State Senate Legislative...

    • data-ocpw.opendata.arcgis.com
    • hub.arcgis.com
    Updated Jan 22, 2020
    + more versions
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    OC Public Works (2020). OCACS 2017 Demographic Characteristics for State Senate Legislative Districts [Dataset]. https://data-ocpw.opendata.arcgis.com/maps/OCPW::ocacs-2017-demographic-characteristics-for-state-senate-legislative-districts
    Explore at:
    Dataset updated
    Jan 22, 2020
    Dataset authored and provided by
    OC Public Works
    Area covered
    Description

    US Census American Community Survey (ACS) 2017, 5-year estimates of the key demographic characteristics of State Senate Legislative Districts (Upper) geographic level in Orange County, California. The data contains 105 fields for the variable groups D01: Sex and age (universe: total population, table X1, 49 fields); D02: Median age by sex and race (universe: total population, table X1, 12 fields); D03: Race (universe: total population, table X2, 8 fields); D04: Race alone or in combination with one or more other races (universe: total population, table X2, 7 fields); D05: Hispanic or Latino and race (universe: total population, table X3, 21 fields), and; D06: Citizen voting age population (universe: citizen, 18 and over, table X5, 8 fields). The US Census geodemographic data are based on the 2017 TigerLines across multiple geographies. The spatial geographies were merged with ACS data tables. See full documentation at the OCACS project github page (https://github.com/ktalexan/OCACS-Geodemographics).

  17. 2024 Florida Senate - Scott vs. Mucarsel-Powell

    • realclearpolling.com
    Updated Apr 11, 2024
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    Real Clear Polling (2024). 2024 Florida Senate - Scott vs. Mucarsel-Powell [Dataset]. https://www.realclearpolling.com/polls/senate/general/2024/florida/scott-vs-mucarsel-powell
    Explore at:
    Dataset updated
    Apr 11, 2024
    Dataset provided by
    RealClearPoliticshttps://realclearpolitics.com/
    Authors
    Real Clear Polling
    Area covered
    Florida
    Description

    2024 Florida Senate - Scott vs. Mucarsel-Powell | RealClearPolling

  18. Washington Post Virginia Poll, October 2007

    • icpsr.umich.edu
    ascii, delimited, sas +2
    Updated Sep 21, 2009
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    The Washington Post (2009). Washington Post Virginia Poll, October 2007 [Dataset]. http://doi.org/10.3886/ICPSR24601.v1
    Explore at:
    sas, spss, delimited, ascii, stataAvailable download formats
    Dataset updated
    Sep 21, 2009
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    The Washington Post
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/24601/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/24601/terms

    Time period covered
    Oct 2007
    Area covered
    United States, Virginia
    Description

    This poll, fielded October 4-8, 2007, is a part of continuing series of monthly polls that solicit public opinion on various political and social issues. This poll focused on Virginia and the state elections. Virginia residents were asked what was the biggest issue facing Virginia at that time, whether they thought the state of Virginia was moving in the right direction, and to rate the condition of Virginia's economy. Several questions asked whether respondents approved of the way the Virginia state legislature was handling its job, and for opinions of Governor Tim Kaine, Senator James Webb, Senator John Warner, the Republicans and Democrats in the state legislature, Junior Senator Mark Warner, Former Governor Jim Gilmore, and Congressman Tom Davis. Respondents were asked how closely they had been following the races for general assembly and state senate in Virginia, how likely they would be to vote in the Virginia state elections and for whom they would vote if the 2008 United States senate race were being held that day, which political party they would like to see in control of the state legislature, and which issues would be most important in their vote for the Virginia state legislature. A series of questions asked respondents about immigration, including how many recent immigrants lived in the respondents' area at the time, how much contact they had with recent immigrants, their opinions of immigrants and how they affect the country, whether illegal immigration was a problem in their area, and how federal, state, and local governments should handle illegal immigration issues. Information was also collected on how closely respondents were following the 2008 presidential race, how likely they were to vote in the 2008 presidential primaries in their state, for whom respondents would vote if the Democratic and Republican primaries and presidential election were being held that day, and for their opinions on the 2008 potential presidential candidates. Respondents were asked which political party they trusted more to handle issues such as taxes and the war in Iraq, which political party they preferred the next president to belong to, as well as whether they approved of the way George W. Bush was handling the presidency. Additional topics included the Iraq War, traffic congestion in their area of the state, Virginia's transportation funding plan, and Virginia's law on abusive driver fees. Demographic information includes sex, age, race, education level, household income, religious preference, frequency of religious attendance, whether respondents considered themselves to be a born-again Christian, whether anyone in the household was a military veteran, marital status, type of residential area (e.g., urban or rural), whether respondents were born in the United States, how many years they had lived in the state of Virginia, voter registration status and participation history, political party affiliation, political philosophy, and the presence of children under the age of 18 in the household.

  19. H

    Replication Data for: Electoral predictors of polling errors

    • dataverse.harvard.edu
    Updated Mar 6, 2025
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    Sina Chen (2025). Replication Data for: Electoral predictors of polling errors [Dataset]. http://doi.org/10.7910/DVN/0T9DIZ
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 6, 2025
    Dataset provided by
    Harvard Dataverse
    Authors
    Sina Chen
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Case studies of polling failures focus on within-election differences in poll accuracy. The crucial question of why polls fail in one election but not in others often remains a matter of speculation. To develop a contextual understanding, we review and unify the- ories of election features suspected of encouraging polling errors, including mobilization, candidacies, polarization, and electoral conduct. We extend a Bayesian hierarchical modeling approach that separates poll bias and variance at the election level and links error components to electoral predictors. Investigating 6,375 pre-election polls across 318 U.S. Senate elections, 1990-2022, we find an overall trend toward smaller but more uniform errors. Poll variance exhibits a weak negative association with mobilization and polarization. Until 2004, frontrunners and incumbents were overestimated, but there is little evidence that polls are biased for female or minority candidates. Finally, Republicans in states with lower levels of state democracy are slightly underestimated in recent years.

  20. f

    Race/Ethnicity (by Georgia Senate) 2019

    • gisdata.fultoncountyga.gov
    • opendata.atlantaregional.com
    Updated Feb 25, 2021
    Share
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    Race/Ethnicity (by Georgia Senate) 2019 [Dataset]. https://gisdata.fultoncountyga.gov/datasets/GARC::race-ethnicity-by-georgia-senate-2019
    Explore at:
    Dataset updated
    Feb 25, 2021
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    This dataset was developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau.For a deep dive into the data model including every specific metric, see the Infrastructure Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics.Naming conventions:Prefixes: None Countp Percentr Ratem Mediana Mean (average)t Aggregate (total)ch Change in absolute terms (value in t2 - value in t1)pch Percent change ((value in t2 - value in t1) / value in t1)chp Change in percent (percent in t2 - percent in t1)s Significance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computed Suffixes: _e19 Estimate from 2014-19 ACS_m19 Margin of Error from 2014-19 ACS_00_v19 Decennial 2000, re-estimated to 2019 geography_00_19 Change, 2000-19_e10_v19 2006-10 ACS, re-estimated to 2019 geography_m10_v19 Margin of Error from 2006-10 ACS, re-estimated to 2019 geography_e10_19 Change, 2010-19The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2015-2019). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website.Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2015-2019Data License: Creative Commons Attribution 4.0 International (CC by 4.0)Link to the manifest: https://www.arcgis.com/sharing/rest/content/items/3d489c725bb24f52a987b302147c46ee/data

Share
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Close
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Statista (2025). U.S. Senators 1975-2023, by race and ethnicity [Dataset]. https://www.statista.com/statistics/198430/senators-in-the-us-congress-by-ethnic-group-since-1975/
Organization logo

U.S. Senators 1975-2023, by race and ethnicity

Explore at:
Dataset updated
Feb 25, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
United States
Description

There are 100 Senators that serve in the United States Congress at any given time - two from each of the fifty states. As of the first day of the 118th Congress, there were three African American Senators, two Asian American Senators, and six Hispanic Senators.

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